Augmented Table Tennis

EXPERIMEDIA continues to realise CAR’s inspirational ideas for using innovative media technology for high performance sports training in the Augmented Table Tennis experiment. CAR’s vision for table tennis was outlined in the facilities design concept as shown in the video … Continued

EXPERIMEDIA continues to realise CAR’s inspirational ideas for using innovative media technology for high performance sports training in the Augmented Table Tennis experiment. CAR’s vision for table tennis was outlined in the facilities design concept as shown in the video below:

Using CAR’s design concept and results EXPERIMEDIA’s ethnographic study researchers from Chalmers University of Technology (Gothenburg) and Interactive Institute worked with CAR to define the aims of the experiment:

Explore how technology can enhance professional training in table tennis.

Discover what kind of information is meaningful or too subtle to be directly detected.

Design a prototype of a system which enables augmented feedback to both elite players and coaches.

Test it and find requirements for a further version of the system

The experiment provides an automatic notation analysis system for table tennis based on the capture of the bouncing of the ball on the table through sound or vibration. The data obtained from the bouncing location and time is shown projected on the same table and/or a second screen. Statistics, game zones, accuracy, flight time or winning points, can be shown in real-time or after the game to analyse what happened. All the team can be involved in the discussion—athletes, coaches and technical and scientific staff—to help the process to be more efficient.
The way the data can be analysed will change forever the point of view of discussing the game of table tennis.

The experiment used focus group’s to co-create three basic scenarios where the technology could be applied:

Target training:the scenario has two players (or one player and one assistant) where the trainee has to practice a particular kind of stroke returning the ball in a specific area for a certain amount of times. The area, the number of times and the repetitions of the exercise are set by the assistant. At the end of each repetition, information about the practice was shown on the table and on the screen. The stakeholder required to display a percentage of success, coded with a specific colour. The motivation behind this scenario is to quantify the precision of the player.

Service Training: the scenario has the presence of one player, practicing the service. The system displays the hits on the table with a relative ID to show the order and the time differences between the bounces on the screen. The trainer sets the number of services to be practiced. The scenario has the goals of representing exactly where the ball is bouncing (difficult to be seen from the player perspective) and shorten the time between the first two bounces. The coach wants also to use it to experiment a hypothesis that he elaborated about associating different time differences according the kind of spin applied.

Point Patterns: the players play a rally (one point) and the system shows who wins it, and using lines and circles it should represent the situation of the point just played. It was agreed to use a gradient scale to colour the lines to code the time of the hits (from cold colours for older hits till warm colours for the recent ones). The goal of the scenario is to try to represent the gameplay of the players and make post-game analysis.

This first pilot opens new opportunities to share this information with TV in case of Live events or through colleagues and team using images and data. The way metadata is projected over the table or thru complementary screen will enhance the information of the game and will become and attractive asset for TV Broadcasting giving a new way of looking at table tennis in major competitions. Statistics, Accuracy rating, game areas or playing tendencies would be shown in teal time or at the end of the rally to give and augmented reality of the game for the spectators.
On the other hand the same capability could be used on the daily training process using this additional information to enrich the discussion between athletes and coaches and scientific staff that at the end of the day will mean increase the benefits on the learning curve of the team and the sport through augmented reality information.